Will AI really improve productivity?

Nobel laureate Paul Krugman argues that?AI would not have any sizeable impact on the American economy for at least another decade. Maybe not.

Krugman makes the case that productivity tends to leg new technologies because firms need time to adjust their processes to those technologies. Before digital transformation projects were electrical transformation and typewriter transformation. However fast the adoption, productivity takes some minimum amount of time to increase as organisations figure out how to use the technology and build the infrastructure to support it.?

Indeed, as the chart below shows, electricity was introduced into use in 1892 and we didn’t see a rise in productivity growth until 1920, nearly three decades later. In that time, factories had to be entirely redesigned and assembly lines assembled. (And, roughly, in the era of electrification productivity growth accelerated most as electricity adoption approached 25% of households.)

In the Information Technology revolution, workplaces had to be entirely rethought, rebuilt. Computers were introduced more widely in the 1970s and 1980s to American businesses, preceding an increase in productivity growth. (I don’t show computer penetration for ease of understanding).?

We see another spike in productivity growth when Internet penetration passes 25% of American households.?I take this 25% level to reflect two things: the first is sufficient time for sufficient learning about the technology for firms to use it usefully and enough penetration to actually have an impact on day-to-day activities.

But why would AI be any different to electrification or IT which took decades to have an impact? (And, in the case of IT, whose impact was short-lived?)?

First, getting this technology in the door is pretty easy. Unlike electricity, or even the Internet, AI services will be available without having to build new infrastructure (or even insert an AOL CD into one’s PC). ChatGPT, for one,?is spreading at an unprecedented speed:?it took only 60 days to go from 1m to 100m users?and in March saw more than 1.5bn visits. In my discussions with LLM vendors, systems integrators, consultancies and firms themselves, using generative AI tools is an exceptionally high priority. They are already persuaded.

Second, companies are ready for AI. Three decades of business process reengineering, outsourcing and digitisation have meant firms are better positioned than ever to make changes to functions. In many cases, an LLM used to triage inbound customer requests will simply replace an old-school keyword-based system. The LLM will just handle 95% of inbound tasks without human intervention when the previous tool handled 60% automatically. Plugging an LLM in is much easier than?replacing a steam-powered drive shaft with snaking cables of alternating current.

Will this mean a quicker shift in productivity? There are many other confounding factors that could drag productivity growth back to earth. But all other things being equal, the conditions may be ripe for a surge.

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